{
 "cells": [
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   "source": [
    "# 2. 线性代数（基于Python）\n",
    "各位同学大家好，欢迎大家来到《线性代数》的世界，上一章《高等数学》我们讨论了许多研究函数的工具，说到底，函数相对是一个连续的世界. 然而事实上，现实世界有很多事情不是连续的，例如当我们拍了一张照片，如果把我们看着是连续变化的图像在电脑上不断放大，你会发现其实是有一个个非常小的像素格组成的，这就是我们在计算中经常使用的一种近似方法，将连续的事物离散化，方便计算机计算.所以在这门课中，我们会讲述离散世界的研究工具，向量、矩阵等等，那我们就开始我们今天的课程吧！\n",
    "\n",
    "本章的主要内容如下：\n",
    "\n",
    "1. 理论知识：\n",
    "- 线性方程组与向量\n",
    "- 向量空间、矩阵、行列式以及范数\n",
    "- 对角化、矩阵的特征值与特征向量、正交化\n",
    "\n",
    "2. 实战案例：\n",
    "- Ginger的智慧农场I——图像的基本处理\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "64e799d9",
   "metadata": {},
   "source": [
    "### 2.1 线性方程组与向量\n",
    "<div class=\"alert alert-info\" role=\"alert\">\n",
    "❓ GitModel 公司的实习生Ginger自己在家中后院组建了一个智慧农场，养了几只公鸡和兔子，由于刚来实习，还不会很深的模型，采用的摄像头对动物计数时候，只能统计有多少个头，有多少只脚.现在摄像头采集到的数据是一共有10个头，28只脚，请问鸡兔各有几只？\n",
    "</div>\n",
    "我们可以列出一个二元一次方程，假设鸡有$x$只，兔子有$y$只那么可以得到\n",
    "\n",
    "$$\n",
    "\\left\\{\\begin{array}{l}\n",
    "x+y=10 \\\\\n",
    "2x+4y=28\n",
    "\\end{array}\\right.\\label{eq1}\n",
    "$$\n",
    "\n",
    "#### 2.1.1 线性方程组\n",
    "$(\\ref{eq1})$在中学阶段叫做二元一次方程组，当然解这个方程组很简单，答案是：$\\left\\{\\begin{array}{l}x=6 \\\\ y=4\\end{array}\\right.$.\n",
    "现在我们忘记中学阶段解二元一次方程组的高斯消元法，把二元一次方程组的本质抽象出来，探讨一种解决二元一次方程组的方法.通过观察，我们发现：二元一次方程组的未知数的阶数都是一次，式子两边都是用等式相连，因此我们给这个方程组起另一个名字：**线性方程组**.在前面的线性方程组中，事实上可以看成是一张表格，\n",
    "\n",
    "| $x$的系数 | $y$的系数 | 结果 |\n",
    "|:---------:|:---------:|:----:|\n",
    "|     1     |     1     |  10  |\n",
    "|     2     |     4     |  28  |\n",
    "\n",
    "我们把同一个未知数的系数放在一起，并且每个变量的系数都用一个**向量**表示，如把$x$的系数放在一起，就是$\\left[\\begin{array}{l}1\\\\2\\end{array}\\right]$,类似的，我们把$y$的系数也放在一起，得到$\\left[\\begin{array}{l}1\\\\4\\end{array}\\right]$. 最后，如果我们把所有数值都移到等式的左边，使得方程组中每个等式右边都为零，那么结果事实上可以看成是$1$的系数，称为常数项，如果我们也放在一起，得到$\\left[\\begin{array}{l}10\\\\28\\end{array}\\right]$.最终，我们的方程组$(\\ref{eq1})$可以用向量形式表示成\n",
    "\n",
    "$$\n",
    "\\left\\{\\begin{array}{l}\n",
    "x+y=10\\\\\n",
    "2x+4y=28\n",
    "\\end{array}\\right.\n",
    "\\Rightarrow\n",
    "\\begin{bmatrix}\n",
    "{1}\\\\\n",
    "{2}\\\\\n",
    "\\end{bmatrix}\n",
    "x+\\begin{bmatrix}\n",
    "{1}\\\\\n",
    "{4}\\\\\n",
    "\\end{bmatrix}\n",
    "y = \\begin{bmatrix}\n",
    "{10}\\\\\n",
    "{28}\\\\\n",
    "\\end{bmatrix}\\label{eq*}\n",
    "$$\n",
    "\n",
    "如果我们将前面包含未知数的两个向量拼接在一起，可以得到一个二维的数表\n",
    "$$\\begin{bmatrix}\n",
    "{1\\quad1}\\\\\n",
    "{2\\quad4}\\\\\n",
    "\\end{bmatrix}$$\n",
    "像这样的数表我们以后将其称为**矩阵**，由于在方程组中，这个矩阵表示的是未知数的系数，故称为系数矩阵，常用$\\mathbf{A}$表示.结果向量也称为常数向量，通常记作$b$.\n",
    "\n",
    "下面我们尝试使用python解线性方程组，```Numpy```中已经封装了求解线性方程组的函数，我们仅需要传入对应的系数矩阵$\\mathbf{A}$以及常数向量$b$，程序就会算出相应的结果."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "caed8718",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T13:35:36.844186Z",
     "start_time": "2022-05-27T13:35:34.502255Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "线性方程组的解为：\n",
      " [6. 4.]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np \n",
    "A = np.array([[1, 1],\n",
    "              [2, 4]])     # 将系数所有向量拼在一起\n",
    "b = np.array([10,\n",
    "              28])  # 常数向量\n",
    "x = np.linalg.solve(A,b)   # 解线性方程组\n",
    "print(\"线性方程组的解为：\\n\",x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44e5f67d",
   "metadata": {},
   "source": [
    "## 2.2 向量空间、矩阵、行列式以及范数"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3bd71d1d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-18T13:15:28.811386Z",
     "start_time": "2022-05-18T13:15:28.801157Z"
    }
   },
   "source": [
    "<div class=\"alert alert-info\" role=\"alert\">\n",
    "❓ 然而，Ginger希望多养几种动物，近日他又引入了几只公鸡和几只鸭子，现在采集到的数据是一共有14个头，40只脚，请问鸡兔鸭各有几只？\n",
    "</div>\n",
    "\n",
    "假设鸭子的数目是$z$只，我们直接列出方程组\n",
    "$$\n",
    "\\left\\{\\begin{array}{l}\n",
    "x + y + z = 14 \\\\\n",
    "2x+4y + 2z = 40\n",
    "\\end{array}\\right.\\label{eq2}\n",
    "$$\n",
    "\n",
    "我们直接采用Python求解："
   ]
  },
  {
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   "execution_count": 2,
   "id": "7f09a2b7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T13:35:37.969175Z",
     "start_time": "2022-05-27T13:35:36.848144Z"
    }
   },
   "outputs": [
    {
     "ename": "LinAlgError",
     "evalue": "Last 2 dimensions of the array must be square",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mLinAlgError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_1744/1764143189.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      3\u001b[0m b = np.array([14,\n\u001b[0;32m      4\u001b[0m               40])  # 常数向量\n\u001b[1;32m----> 5\u001b[1;33m \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlinalg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msolve\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m)\u001b[0m   \u001b[1;31m# 解线性方程组\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"线性方程组的解为：\\n\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<__array_function__ internals>\u001b[0m in \u001b[0;36msolve\u001b[1;34m(*args, **kwargs)\u001b[0m\n",
      "\u001b[1;32mD:\\conda3\\envs\\ML38\\lib\\site-packages\\numpy\\linalg\\linalg.py\u001b[0m in \u001b[0;36msolve\u001b[1;34m(a, b)\u001b[0m\n\u001b[0;32m    378\u001b[0m     \u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_makearray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    379\u001b[0m     \u001b[0m_assert_stacked_2d\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 380\u001b[1;33m     \u001b[0m_assert_stacked_square\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    381\u001b[0m     \u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mwrap\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_makearray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    382\u001b[0m     \u001b[0mt\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresult_t\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_commonType\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mb\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\conda3\\envs\\ML38\\lib\\site-packages\\numpy\\linalg\\linalg.py\u001b[0m in \u001b[0;36m_assert_stacked_square\u001b[1;34m(*arrays)\u001b[0m\n\u001b[0;32m    201\u001b[0m         \u001b[0mm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mn\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    202\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mm\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mn\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 203\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0mLinAlgError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Last 2 dimensions of the array must be square'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    204\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    205\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_assert_finite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0marrays\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mLinAlgError\u001b[0m: Last 2 dimensions of the array must be square"
     ]
    }
   ],
   "source": [
    "A = np.array([[1, 1, 1],\n",
    "              [2, 4, 2]])     # 将系数所有向量拼在一起\n",
    "b = np.array([14,\n",
    "              40])  # 常数向量\n",
    "x = np.linalg.solve(A,b)   # 解线性方程组\n",
    "print(\"线性方程组的解为：\\n\",x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebc2fd02",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-danger\" role=\"alert\">\n",
    "这个代码一定会报错！它的报错原因说，一定要求系数矩阵是个方阵，这是因为要确定的求解一个多元方程组，有多少个未知数，就需要有多少个方程！所以系数矩阵一定是个方阵.\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43fc6856",
   "metadata": {},
   "source": [
    "那么，如果我们加入动物眼睛的统计数据，方程组可以为：\n",
    "\n",
    "$$\n",
    "\\left\\{\\begin{array}{l}\n",
    "x + y + z = 14 \\\\\n",
    "2x+4y + 2z = 40 \\\\\n",
    "2x + 2y + 2z = 28\n",
    "\\end{array}\\right.\\label{eq5}\n",
    "$$\n",
    "我们现在再去看每个变量的系数向量，实际上被推广到了三阶，当实际生活中动物越来越多时，我们需要引入的变量也越来越多，所以我们需要引入更高维度的向量来表达我们的问题.一般地，我们研究的问题，变量的个数都是有限的，所以我们一般研究的向量都是有限维的向量，一般称为**n维向量**.\n",
    "\n",
    "继续使用python求解$\\eqref{eq5}$的问题"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "50c88627",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T13:35:53.998162Z",
     "start_time": "2022-05-27T13:35:53.967269Z"
    }
   },
   "outputs": [
    {
     "ename": "LinAlgError",
     "evalue": "Singular matrix",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mLinAlgError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_1744/4287143981.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      5\u001b[0m               \u001b[1;36m40\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      6\u001b[0m               28])  # 常数向量\n\u001b[1;32m----> 7\u001b[1;33m \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlinalg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msolve\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m)\u001b[0m   \u001b[1;31m# 解线性方程组\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      8\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"线性方程组的解为：\\n\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<__array_function__ internals>\u001b[0m in \u001b[0;36msolve\u001b[1;34m(*args, **kwargs)\u001b[0m\n",
      "\u001b[1;32mD:\\conda3\\envs\\ML38\\lib\\site-packages\\numpy\\linalg\\linalg.py\u001b[0m in \u001b[0;36msolve\u001b[1;34m(a, b)\u001b[0m\n\u001b[0;32m    391\u001b[0m     \u001b[0msignature\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'DD->D'\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0misComplexType\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mt\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32melse\u001b[0m \u001b[1;34m'dd->d'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    392\u001b[0m     \u001b[0mextobj\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mget_linalg_error_extobj\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0m_raise_linalgerror_singular\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 393\u001b[1;33m     \u001b[0mr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgufunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0msignature\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0msignature\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mextobj\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mextobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    394\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    395\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mwrap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresult_t\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\conda3\\envs\\ML38\\lib\\site-packages\\numpy\\linalg\\linalg.py\u001b[0m in \u001b[0;36m_raise_linalgerror_singular\u001b[1;34m(err, flag)\u001b[0m\n\u001b[0;32m     86\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     87\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_raise_linalgerror_singular\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0merr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mflag\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 88\u001b[1;33m     \u001b[1;32mraise\u001b[0m \u001b[0mLinAlgError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Singular matrix\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     89\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     90\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_raise_linalgerror_nonposdef\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0merr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mflag\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mLinAlgError\u001b[0m: Singular matrix"
     ]
    }
   ],
   "source": [
    "A = np.array([[1, 1, 1],\n",
    "              [2, 4, 2],\n",
    "              [2, 2, 2]])     # 将系数所有向量拼在一起\n",
    "b = np.array([14,\n",
    "              40,\n",
    "              28])  # 常数向量\n",
    "x = np.linalg.solve(A,b)   # 解线性方程组\n",
    "print(\"线性方程组的解为：\\n\",x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15dce4ac",
   "metadata": {},
   "source": [
    "发现事实上还是报错，只不过这次报错的原因是```Singular matrix```，意思是系数矩阵是**奇异的**，或者说是**退化的**.如果观察方程组$\\eqref{eq3}$，你会发现其实第三个式子是第一个式子的2倍导出的，如果我们采用高斯消元法求解方程，那么将式子1的-2倍加到第3个式子，第三个式子就为0了.这说明我们新增的这个式子对于解方程实际上起不到任何作用的，因为它的信息已经被囊括在第一个式子中了.\n",
    "\n",
    "于是现在我们需要解决的问题有两个：\n",
    "1. 当求解n个未知数时，方程组要满足什么条件，才是有解的？\n",
    "2. 当我们将向量推广到高维之后，向量之间的计算是满足的吗？"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ba38e3c",
   "metadata": {},
   "source": [
    "### 2.2.1 向量的运算法则\n",
    "从上面的方程组改写成向量的表达形式时，大家心中也许会想问一个问题：这两种写法是等价的吗？我们看$\\eqref{eq*}$的计算过程：\n",
    "$$\n",
    "\\begin{bmatrix}\n",
    "{1}\\\\\n",
    "{2}\\\\\n",
    "\\end{bmatrix}\n",
    "x+\\begin{bmatrix}\n",
    "{1}\\\\\n",
    "{4}\\\\\n",
    "\\end{bmatrix}\n",
    "y = \\begin{bmatrix}\n",
    "{10}\\\\\n",
    "{28}\\\\\n",
    "\\end{bmatrix}\n",
    "\\Rightarrow\n",
    "\\begin{bmatrix}\n",
    "{x}\\\\\n",
    "{2x}\\\\\n",
    "\\end{bmatrix}\n",
    "+\\begin{bmatrix}\n",
    "{y}\\\\\n",
    "{4y}\\\\\n",
    "\\end{bmatrix}\n",
    " = \\begin{bmatrix}\n",
    "{10}\\\\\n",
    "{28}\\\\\n",
    "\\end{bmatrix}\n",
    "$$\n",
    "由于要保证对应的分量相等，所以自然我们就可以恢复出方程$\\eqref{eq1}$.\n",
    "上面这个过程，向量的计算有两种：\n",
    "- 一个数乘一个向量；\n",
    "- 一个向量加一个向量；\n",
    "显然，当变量个数变多之后，也会满足上面这两种运算法则，因此我们接下来正式引入向量的基本运算法则：\n",
    "\n",
    "给定$n$维向量\n",
    "$$\n",
    "x= \\begin{bmatrix}\n",
    "{x_1}\\\\\n",
    "{x_2}\\\\\n",
    "{\\vdots}\\\\\n",
    "{x_n}\n",
    "\\end{bmatrix},\n",
    "y= \\begin{bmatrix}\n",
    "{y_1}\\\\\n",
    "{y_2}\\\\\n",
    "{\\vdots}\\\\\n",
    "{y_n}\n",
    "\\end{bmatrix}\n",
    "$$\n",
    "- 向量的加法定义为：\n",
    "$$\n",
    "x+y = \\begin{bmatrix}\n",
    "{x_1 + y_1}\\\\\n",
    "{x_2 + y_2}\\\\\n",
    "{\\vdots}\\\\\n",
    "{x_n + y_n}\n",
    "\\end{bmatrix},\n",
    "$$\n",
    "即两个向量对应的分量相加.\n",
    "\n",
    "- 向量的数乘定义为：\n",
    "对于$k \\in \\mathbf{R}$,\n",
    "$$\n",
    "kx = \\begin{bmatrix}\n",
    "{kx_1 }\\\\\n",
    "{kx_2}\\\\\n",
    "{\\vdots}\\\\\n",
    "{kx_n}\n",
    "\\end{bmatrix},\n",
    "$$\n",
    "即每个分量都乘上$k$.\n",
    "\n",
    "关于向量与向量的乘法，在后续的学习中，我们再进一步介绍.我们约定一个使用习惯，我们默认所有的向量都采用列向量的形式，如上面所示.当我们在文中书写时，为了排版优美，通常将向量由列向量转成行向量进行书写，向量的行列交换的称为向量的**转置**，记做$x^T = (x_1, x_2, \\cdots, x_n)$.我们使用```Numpy```实现向量之间的基本计算."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "dd8c3934",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T13:36:01.359821Z",
     "start_time": "2022-05-27T13:36:01.339853Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x=[1 2 3],y=[4 5 6]\n",
      "x的维度为(3,)\n",
      "x+y = [5 7 9]\n",
      "kx = [3 6 9]\n",
      "3x+2y =[11 16 21] \n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "# 生成向量\n",
    "x = np.array([1, 2, 3]) # array默认如果只有一列，就是一个向量\n",
    "y = np.array([4, 5, 6])\n",
    "print(\"x={},y={}\".format(x, y))\n",
    "print(\"x的维度为{}\".format(x.shape)) # shape函数用于显示向量的维度，如果是向量默认只有一维，维度显示为(dim,)\n",
    "\n",
    "# 向量加法\n",
    "print(\"x+y = {}\".format(x + y))\n",
    "\n",
    "# 向量数乘\n",
    "k = 3\n",
    "print(\"kx = {}\".format(k*x))\n",
    "\n",
    "print(\"3x+2y ={} \".format(3*x + 2*y))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77095609",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-18T15:37:55.362301Z",
     "start_time": "2022-05-18T15:37:55.356317Z"
    }
   },
   "source": [
    "我们从几何角度来看这个事情，看看向量的加法与数乘在做什么：\n",
    "![](./figures/2-1.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c092f226",
   "metadata": {},
   "source": [
    "做好前面的铺垫后，现在我们可以把空间的概念引进来. 在二维空间中，更准确的说在几何空间中，空间存在无数个类似于$[x_1,y_1],[x_2,y_2]$的几何向量，同时空间中还存在控制几何向量之间的相互关系的运算：加法与数乘.举个不太恰当的例子：人类社会中，除了有存在空间中的人以外，还存在着约束每个人的道德与法律.那么n维空间也是一样的，里面存在着无数个n维向量$(x_1,x_2,...,x_n)^T,(y_1,y_2,...,y_n)^T$，同时存在约束着这些向量运算规则的加法和数乘.\n",
    "\n",
    "至此我们已经回答了第(2)个问题，高维的向量只要是有限维的都是满足我们上面加法与数乘的运算法则的.下面我们想来讨论，对于多个未知数的方程组，什么样的方程组才是有解的？\n",
    "\n",
    "### 2.2.2 向量的线性相关与线性无关"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9ceb2fa",
   "metadata": {},
   "source": [
    "首先我们需要介绍几个研究向量的工具，我们先来看方程组$\\eqref{eq5}$为什么没有解，主要的原因是：从式子化简的结果来说，第一个式子跟第三个式子表达的是一个意思.看另外一个例子\n",
    "$$\n",
    "\\left\\{\\begin{array}{l}\n",
    "x + y + z = 14 \\\\\n",
    "2x+4y + 2z = 40 \\\\\n",
    "3x + 5y + 3z = 54\n",
    "\\end{array}\\right.\\label{eq10}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15496a82",
   "metadata": {},
   "source": [
    "这个方程组，如果你尝试求解的话也会显示```Singular matrix```，仔细观察就会发现第三个式子是由，第一个式子和第二个式子相加得到的，所以第三个式子的信息已经包含在上面两个式子中了，那么我们如何才能一眼看出“式子是有效的”呢？我们拿出一件工具——**向量的线性相关与线性无关**.\n",
    "给定一组向量$(\\alpha_1, \\alpha_2, \\cdots, \\alpha_k)$（注意，这个地方之所以没有转置符号，是因为这是一个向量组，每个$\\alpha$都是一个列向量，需要与向量的写法做区分），对于向量$\\beta$，如果能被存在一组不全为0的常数$m_1, m_2, \\cdots, m_k$，使得\n",
    "$$\\beta = m_1\\alpha_1 + m_2\\alpha_2 + \\cdots + m_k\\alpha_k$$\n",
    "则称向量$\\beta$与向量组$(\\alpha_1, \\alpha_2, \\cdots, \\alpha_k)$是线性相关的，或称$\\beta$可以被向量组$(\\alpha_1, \\alpha_2, \\cdots, \\alpha_k)$线性表出.一旦向量是线性相关的，也就说明“$\\beta$是一个多余的向量，因为它可以由其他的向量去表示”.\n",
    "\n",
    "对于方程组$\\eqref{eq10}$,如果我们把第$i$个方程当成是一个向量$\\alpha_i$（这是不严谨的说法），则$\\alpha_3 = \\alpha_1 + \\alpha_2$，因此第三个方程是多余的.\n",
    "\n",
    "反之，如果$$m_0\\beta + m_1\\alpha_1 + m_2\\alpha_2 + \\cdots + m_k\\alpha_k = 0$$当且仅当$m_0, m_1, m_2, \\cdots, m_k$全都为0，则称$\\beta, \\alpha_1, \\alpha_2, \\cdots, \\alpha_k$是线性无关的."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a52a4bba",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-18T16:10:02.677008Z",
     "start_time": "2022-05-18T16:10:02.673016Z"
    }
   },
   "source": [
    "到目前为止，判断一个方程组有唯一解我们有两条法则：\n",
    "- $n$个未知数要有$n$个方程\n",
    "- 可以使用线性无关去判断“有效的方程”\n",
    "\n",
    "然而，如果当一个方程组未知数的量很大之后，你需要去判断哪些方程是“有效的”也是一件非常花时间的工作，有没有一个更好的方法呢，答案是有的，我们先介绍**行列式的概念**.在2.1.1中我们已经介绍了矩阵就是一种数表，而对于我们现在的问题而言，系数矩阵$A$总是行数、列数相等的，因为它的方程个数等于未知数的个数，像这样行数等于列数的矩阵我们称为**方阵**.对于方阵而言，我们可以计算它的行列式$|A|$，用```Numpy```实现如下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a6dd2b9b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T13:36:27.183148Z",
     "start_time": "2022-05-27T13:36:27.160210Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A的行列式的值为： 0.0\n",
      "B的行列式的值为： -2.0\n"
     ]
    }
   ],
   "source": [
    "A = np.array([[1, 1, 1],\n",
    "              [2, 4, 2],\n",
    "              [2, 2, 2]])\n",
    "\n",
    "np.linalg.det(A) # 计算方阵A的行列式\n",
    "print(\"A的行列式的值为：\",np.linalg.det(A))\n",
    "\n",
    "B = np.array([[1,1,1,1],\n",
    "              [1,2,0,0],\n",
    "              [1,0,3,0],\n",
    "              [1,0,0,4]])\n",
    "B_det = np.linalg.det(B)\n",
    "print(\"B的行列式的值为：\",B_det)\n",
    "\n",
    "# B = np.array([[1,1,1,1],\n",
    "#               [1,2,0,0],\n",
    "#               [1,0,0,4]])# 你可以尝试用非方阵计算行列式，压根没法算！"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9c0122a",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-danger\" role=\"alert\">\n",
    "注意：一定要是方阵才能求行列式！\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f12a8a0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-18T16:23:09.079332Z",
     "start_time": "2022-05-18T16:23:09.073121Z"
    }
   },
   "source": [
    "有了行列式之后，以后只要我们判断了一个方程组：\n",
    "1. 未知数个数等于方程的个数\n",
    "2. 系数行列式$|A| \\neq 0$\n",
    "则这个方程组是有唯一解的.\n",
    "\n",
    "上面这个判断的法则就是著名的**克莱姆法则(Cramer's Rule)**，更重要的是，克莱姆法则提出了一种解的结构：\n",
    "\n",
    "设线性方程组的表达式为：$\\left\\{\\begin{array}{c}a_{11} x_{1}+a_{12} x_{2}+\\cdots+a_{1 n} x_{n}=b_{1} \\\\ a_{21} x_{1}+a_{22} x_{2}+\\cdots+a_{2 n} x_{n}=b_{2} \\\\ \\cdots \\cdots \\\\ a_{n 1} x_{1}+a_{n 2} x_{2}+\\cdots+a_{n n} x_{n}=b_{n}\\end{array}\\right.$\n",
    "，系数行列式为：$D = \\left|\\begin{array}{cccc}a_{11} & a_{12} & \\cdots & a_{1 n} \\\\ a_{21} & a_{22} & \\cdots & a_{2 n} \\\\ \\cdots & \\cdots & \\cdots & \\cdots \\\\ a_{n 1} & a_{n 2} & \\cdots & a_{m n}\\end{array}\\right| \\neq 0$，则该线性方程组有且仅有唯一解:\n",
    "\n",
    "$$\n",
    "x_{1}=\\frac{D_{1}}{D}, x_{2}=\\frac{D_{2}}{D}, \\cdots, x_{n}=\\frac{D_{n}}{D}\n",
    "$$\n",
    "\n",
    "其中，$D_{j}=\\left|\\begin{array}{ccccccc}a_{11} & \\cdots & a_{1, j-1} & b_{1} & a_{1, j+1} & \\cdots & a_{1 n} \\\\ a_{21} & \\cdots & a_{2, j-1} & b_{2} & a_{2, j+1} & \\cdots & a_{2 n} \\\\ \\cdots & \\cdots & \\cdots & \\cdots & \\cdots & \\cdots & \\cdots \\\\ a_{n 1} & \\cdots & a_{n, j-1} & b_{n} & a_{n, j+1} & \\cdots & a_{n n}\\end{array}\\right|$\n",
    "\n",
    "<div class=\"alert alert-info\" role=\"alert\">\n",
    "🌰举个例子：\n",
    "解线性方程组 $\\left\\{\\begin{array}{l}2 x_{1}+x_{2}-5 x_{3}+x_{4}=8 \\\\ x_{1}-3 x_{2}-6 x_{4}=9 \\\\ 2 x_{2}-x_{3}+2 x_{4}=-5 \\\\ x_{1}+4 x_{2}-7 x_{3}+6 x_{4}=0\\end{array}\\right.$\n",
    "</div>\n",
    "\n",
    "**解：**方程组的系数行列式\n",
    "$$\n",
    "D=\\left|\\begin{array}{cccc}\n",
    "2 & 1 & -5 & 1 \\\\\n",
    "1 & -3 & 0 & -6 \\\\\n",
    "0 & 2 & -1 & 2 \\\\\n",
    "1 & 4 & -7 & 6\n",
    "\\end{array}\\right|=27 \\neq 0\n",
    "$$\n",
    "由克莱姆法则知：方程组有唯一解.\n",
    "\n",
    "$D_{1}=\\left|\\begin{array}{cccc}8 & 1 & -5 & 1 \\\\ 9 & -3 & 0 & -6 \\\\ -5 & 2 & -1 & 2 \\\\ 0 & 4 & -7 & 6\\end{array}\\right|=81 \\Rightarrow x_{1}=\\frac{D_{1}}{D}=\\frac{81}{27} = 3$，\n",
    "$D_{2}=\\left|\\begin{array}{cccc}2 & 8 & -5 & 1 \\\\ 1 & 9 & 0 & -6 \\\\ 0 & -5 & -1 & 2 \\\\ 1 & 0 & -7 & 6\\end{array}\\right|=-108 \\Rightarrow x_{2}=\\frac{D_{2}}{D} =\\frac{-108}{27}= 4$，$D_{3}=\\left|\\begin{array}{cccc}2 & 1 & 8 & 1 \\\\ 1 & -3 & 9 & -6 \\\\ 0 & 2 & -5 & 2 \\\\ 1 & 4 & 0 & 6\\end{array}\\right|=-27 \\Rightarrow x_{3}=\\frac{D_{3}}{D} = =\\frac{-27}{27}=-1$，$D_{4}=\\left|\\begin{array}{cccc}2 & 1 & -5 & 8 \\\\ 1 & -3 & 0 & 9 \\\\ 0 & 2 & -1 & -5 \\\\ 1 & 4 & -7 & 0\\end{array}\\right|=27 \\Rightarrow x_{4}=\\frac{D_{4}}{D} = \\frac{27}{27} = 1$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "92dcba29",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T13:36:34.437617Z",
     "start_time": "2022-05-27T13:36:34.413640Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "克拉默法则解线性方程组的解为：\n",
      " x1=3.00,\n",
      " x2=-4.00,\n",
      " x3=-1.00,\n",
      " x4=1.00\n"
     ]
    }
   ],
   "source": [
    "# 使用python实现克拉默法则：\n",
    "D = np.array([[2.,1,-5,1],[1,-3,0,-6],[0,2,-1,2],[1,4,-7,6]])\n",
    "D_det = np.linalg.det(D)\n",
    "\n",
    "D1 = np.array([[8.,1,-5,1],[9,-3,0,-6],[-5,2,-1,2],[0,4,-7,6]])\n",
    "D1_det = np.linalg.det(D1)\n",
    "\n",
    "D2 = np.array([[2.,8,-5,1],[1,9,0,-6],[0,-5,-1,2],[1,0,-7,6]])\n",
    "D2_det = np.linalg.det(D2)\n",
    "\n",
    "D3 = np.array([[2.,1,8,1],[1,-3,9,-6],[0,2,-5,2],[1,4,0,6]])\n",
    "D3_det = np.linalg.det(D3)\n",
    "\n",
    "D4 = np.array([[2.,1,-5,8],[1,-3,0,9],[0,2,-1,-5],[1,4,-7,0]])\n",
    "D4_det = np.linalg.det(D4)\n",
    "\n",
    "x1 = D1_det / D_det\n",
    "x2 = D2_det / D_det\n",
    "x3 = D3_det / D_det\n",
    "x4 = D4_det / D_det\n",
    "print(\"克拉默法则解线性方程组的解为：\\n x1={:.2f},\\n x2={:.2f},\\n x3={:.2f},\\n x4={:.2f}\".format(x1,x2,x3,x4))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7c47716",
   "metadata": {},
   "source": [
    "事实上从用的角度上说，这事到这里就结束了，但是你会发现我们还没说行列式是什么:)\n",
    "\n",
    "下面我们详细介绍行列式的概念.[如果你看到数学就头晕目眩，可以直接跳到2.2.3]\n",
    "\n",
    "先看一个式子: $D_{2}=\\left|\\begin{array}{ll}a_{11} & a_{12} \\\\ a_{21} & a_{22}\\end{array}\\right|$. 我们称其为 2 阶行列式,其中 $a_{i j}$ 的第一个下标 $i$ 表示此元素所在的行数,第二个下标 $j$ 表示此元素所在的列数, $i=1,2, j=1,2$,于是此行列式中有四个元素,并且 $\\left|\\begin{array}{ll}a_{11} & a_{12} \\\\ a_{21} & a_{22}\\end{array}\\right|=$ $a_{11} a_{22}-a_{12} a_{21} .$ 这是一个什么样的计算规则 $?$ 它背后有什么样的意义?\n",
    "\n",
    "将此行列式的第 1 行的两个元素 $a_{11}, a_{12}$ 看成一个 2 维向量$\\left[a_{11}, a_{12}\\right]{:=} \\boldsymbol{\\alpha}_{1}$，第二行的两个元素 $a_{21}, a_{22}$ 看成另一个 2 维向量 $\\left[a_{21}, a_{22}\\right]{:=} \\boldsymbol{\\alpha}_{2}$.不妨设 $\\boldsymbol{\\alpha}_{1}$ 的长度(模)为 $l, \\boldsymbol{\\alpha}_{2}$ 的长度(模)为 $m, \\boldsymbol{\\alpha}_{1}$ 与 $x$ 轴正向的夹角为 $\\alpha, \\boldsymbol{\\alpha}_{2}$ 与 $x$ 轴正向的夹角为 $\\beta$, 于是,如图所示：\n",
    "\n",
    "![jupyter](./figures/2-2.png)\n",
    "\n",
    "则：\n",
    "$$\n",
    "\\begin{aligned}\n",
    "S_{\\square O A B C} &=l \\cdot m \\cdot \\sin (\\beta-\\alpha) \\\\\n",
    "&=l \\cdot m(\\sin \\beta \\cos \\alpha-\\cos \\beta \\sin \\alpha) \\\\\n",
    "&=l \\cos \\alpha \\cdot m \\sin \\beta-l \\sin \\alpha \\cdot m \\cos \\beta \\\\\n",
    "&=a_{11} a_{22}-a_{12} a_{21}\n",
    "\\end{aligned}\n",
    "$$\n",
    "因此：\n",
    "$$\n",
    "\\left|\\begin{array}{ll}\n",
    "a_{11} & a_{12} \\\\\n",
    "a_{21} & a_{22}\n",
    "\\end{array}\\right|=a_{11} a_{22}-a_{12} a_{21}=S_{\\square O A B C}\n",
    "$$\n",
    "我们看到了一个极其直观有趣的结论: 2 阶行列式是由两个 2 维向量组成的,其(运算规则的)结果为 以这两个向量为邻边的平行四边形的面积. 这不仅得出了 2 阶行列式的计算规则，也能够清楚地看到其几何意义.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c2c2074",
   "metadata": {},
   "source": [
    "### 2.2.3 矩阵"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b508aaf",
   "metadata": {},
   "source": [
    "回想一下中学阶段在解方程组的场景：每次将方程组抄一遍，消掉一个未知数，又抄一遍，又消掉一个未知数，又抄一遍······这个过程一直持续，非常麻烦，直到最后一个方程可以被解出来，我们希望有一些更简便的记录方法，下面我们介绍另一个非常强大的工具——**矩阵**，但大家学习矩阵前一定要在心里默念十遍：矩阵不仅仅只是用来解方程！它又非常强大的功能，在后面的章节中，我们将一步一步介绍，在这里我们先介绍一些矩阵的基本运算以及在解方程中的应用."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cbfacf0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T13:16:30.312889Z",
     "start_time": "2022-05-27T13:16:30.302915Z"
    }
   },
   "source": [
    "在之前学过的高斯消元法中，我们对方程有些等价变换，对方程组做了这些变换后，对方程的解是不改变的：\n",
    "$$\n",
    "\\left\\{\\begin{array}{l}\n",
    "x + y + z = 14 \\\\\n",
    "2x+4y + 2z = 40 \n",
    "\\end{array}\\right.\n",
    "\\stackrel{交换两个方程的位置}{\\longrightarrow}\n",
    "\\left\\{\\begin{array}{l}\n",
    "2x+4y + 2z = 40 \\\\\n",
    "x + y + z = 14\n",
    "\\end{array}\\right.\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\left\\{\\begin{array}{l}\n",
    "x + y + z = 14 \\\\\n",
    "2x+4y + 2z = 40 \n",
    "\\end{array}\\right.\n",
    "\\stackrel{等号两边同乘一个非零常数}{\\longrightarrow}\n",
    "\\left\\{\\begin{array}{l}\n",
    "2x + 2y + 2z = 28 \\\\\n",
    "2x+4y + 2z = 40 \n",
    "\\end{array}\\right.\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\left\\{\\begin{array}{l}\n",
    "x + y + z = 14 \\\\\n",
    "2x+4y + 2z = 40 \n",
    "\\end{array}\\right.\n",
    "\\stackrel{一个方程加到另外一个方程上导出一个新方程}{\\longrightarrow}\n",
    "\\left\\{\\begin{array}{l}\n",
    "x + y + z = 14 \\\\\n",
    "2x+4y + 2z = 40 \\\\\n",
    "3x + 5y + 3z = 54\n",
    "\\end{array}\\right.\n",
    "$$\n",
    "\n",
    "\n",
    "如上，**交换两个方程的位置**、**一个方程等号两边同乘一个非零常数$k$**，**一个方程加到另外一个方程上导出一个新方程**，这三种操作显然不会改变方程组的解. 那么我们让计算机知道要做这些操作呢，矩阵建立起了这其中的关系. \n",
    "\n",
    "对于一个矩阵$A$，假设行数为$n$，列数为$m$，则它的维度为$n \\times m$，记作：$A_{n\\times m}$. 当两个矩阵要做**乘法**时，我们要求前一个矩阵的列数要等于后一个矩阵的行数，即：给定$A_{a\\times b},B_{c \\times d}$，若$AB$有意义，则$b=c$，并且结果的维度为$a\\times d$，结果矩阵的第$ij$个元素为：**前一个矩阵的第$i$个行向量与后一个矩阵第$j$个列点乘得到**. 也正是如此，我们不能对矩阵乘法轻易交换顺序，也就是说$AB$不一定等于$BA$，这个一定要注意！\n",
    "我们只需要记住这些前提，剩下的事情交给计算机."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b4bd681d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T13:52:21.580432Z",
     "start_time": "2022-05-27T13:52:21.565452Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A的规模(2, 2)\n",
      "B的规模(2, 3)\n",
      "AB=\n",
      "[[-1  4  1]\n",
      " [ 2  1 -5]]\n"
     ]
    }
   ],
   "source": [
    "A = np.array([[1, 2],\n",
    "              [1, -1]])\n",
    "B = np.array([[1, 2, -3],\n",
    "              [-1, 1, 2]])\n",
    "\n",
    "print(\"A的规模{}\".format(A.shape))\n",
    "print(\"B的规模{}\".format(B.shape))\n",
    "\n",
    "# 计算AB\n",
    "print(\"AB=\\n{}\".format(np.matmul(A, B)))\n",
    "\n",
    "# 计算BA会报错维度不对应\n",
    "# np.matmul(B, A)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "faa785f2",
   "metadata": {},
   "source": [
    "此外，两个维度大小一个矩阵可以做加法，即对应位置元素相加. 一个矩阵乘一个常数等于每个位置的元素都乘这个常数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d80694e5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T13:57:34.358658Z",
     "start_time": "2022-05-27T13:57:34.343655Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A+C = \n",
      " [[2 4]\n",
      " [4 3]]\n",
      "3*A = \n",
      " [[ 3  6]\n",
      " [ 3 -3]]\n"
     ]
    }
   ],
   "source": [
    "A = np.array([[1, 2],\n",
    "              [1, -1]])\n",
    "C = np.array([[1, 2],\n",
    "                [3, 4]])\n",
    "print(\"A+C = \\n\", A + C) # A+C \n",
    "print(\"3*A = \\n\", 3 * A) # 3*A\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc0a9b9b",
   "metadata": {},
   "source": [
    "下面我们介绍一些特殊的矩阵，这些矩阵对应着一些特殊变换.\n",
    "#### 1. **单位矩阵**\n",
    "在矩阵的乘法中，有一种矩阵起着特殊的作用，如同数的乘法中的1，这种矩阵被称为单位矩阵. 它是个方阵，从左上角到右下角的对角线（称为主对角线）上的元素均为1，除此以外全都为0.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "bf8ebede",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T14:08:29.250380Z",
     "start_time": "2022-05-27T14:08:28.795076Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "B =\n",
      " [[ 1  2 -3]\n",
      " [-1  1  2]] \n",
      " E = \n",
      " [[1. 0. 0.]\n",
      " [0. 1. 0.]\n",
      " [0. 0. 1.]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 1.,  2., -3.],\n",
       "       [-1.,  1.,  2.]])"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"B =\\n\", B,\"\\n\", \"E = \\n\", np.eye(3)) # 3阶单位阵\n",
    "\n",
    "np.matmul(B, np.eye(3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c5b8895",
   "metadata": {},
   "source": [
    "#### 2.初等矩阵\n",
    "如果你想让计算机懂得解方程组的三个步骤，首先我们先抽象出一个方程组的系数矩阵$A_{n\\times m} $，假设下面介绍三个操作对应的矩阵变换，称为初等矩阵：\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "ccb5d606",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T14:24:40.203178Z",
     "start_time": "2022-05-27T14:24:40.186224Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A = \n",
      " [[1 1 1]\n",
      " [2 4 2]]\n"
     ]
    }
   ],
   "source": [
    "A = np.array([[1, 1, 1],\n",
    "              [2, 4, 2]])\n",
    "print(\"A = \\n\", A)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f154cb7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T14:23:50.425773Z",
     "start_time": "2022-05-27T14:23:50.405826Z"
    }
   },
   "source": [
    "1. **交换第$i$个与第$j$个方程↔️系数矩阵第$i$行与第$j$行互换↔️左乘一个($P_{n \\times n}$)，$P$为单位阵$E_{n}$第$i$行与第$j$行互换**\n",
    "$$\n",
    "\\left\\{\\begin{array}{l}\n",
    "x + y + z = 14 \\\\\n",
    "2x+4y + 2z = 40 \n",
    "\\end{array}\\right.\n",
    "\\Rightarrow\n",
    "\\left\\{\\begin{array}{l}\n",
    "2x+4y + 2z = 40 \\\\\n",
    "x + y + z = 14\n",
    "\\end{array}\\right.\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "80ae168a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T14:28:06.183156Z",
     "start_time": "2022-05-27T14:28:06.163209Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[2, 4, 2],\n",
       "       [1, 1, 1]])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "P = np.array([[0, 1],\n",
    "              [1, 0]])\n",
    "np.matmul(P, A) # 交换了矩阵的两行"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f6c51ae",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T14:33:51.548919Z",
     "start_time": "2022-05-27T14:33:51.528974Z"
    }
   },
   "source": [
    "2. **第$i$个方程左右乘非零常数$k$倍↔️系数矩阵第$i$行乘$k$↔️左乘一个($P_{n \\times n}$)，$P$为单位阵$E_{n}$第$i$行乘$k$**\n",
    "$$\n",
    "\\left\\{\\begin{array}{l}\n",
    "x + y + z = 14 \\\\\n",
    "2x+4y + 2z = 40 \n",
    "\\end{array}\\right.\n",
    "\\Rightarrow\n",
    "\\left\\{\\begin{array}{l}\n",
    "2x + 2y + 2z = 28 \\\\\n",
    "2x+4y + 2z = 40 \n",
    "\\end{array}\\right.\n",
    "$$\n",
    "[注] 本来应该增广矩阵乘$k$倍，但我们这里仅讨论了系数矩阵，这种做法不太严谨！"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "cd0953ff",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T14:36:20.232507Z",
     "start_time": "2022-05-27T14:36:20.214520Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[2, 2, 2],\n",
       "       [2, 4, 2]])"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "P = np.array([[2, 0],\n",
    "              [0, 1]])\n",
    "np.matmul(P, A) # 第$i$行乘$k$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a29dd00f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T14:58:02.263190Z",
     "start_time": "2022-05-27T14:58:02.243242Z"
    }
   },
   "source": [
    "3. **第$i$个方程加到第$j$个方程中↔️系数矩阵第$i$行加到第$j$行↔️左乘一个($P_{n \\times n}$)，$P$为单位阵$E_{n}$第$i$行加到第$j$行**\n",
    "$$\n",
    "\\left\\{\\begin{array}{l}\n",
    "x + y + z = 14 \\\\\n",
    "2x+4y + 2z = 40 \n",
    "\\end{array}\\right.\n",
    "\\Rightarrow\n",
    "\\left\\{\\begin{array}{l}\n",
    "2x + 2y + 2z = 28 \\\\\n",
    "3x+5y + 3z = 44 \n",
    "\\end{array}\\right.\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "a59b5b35",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T14:58:28.231454Z",
     "start_time": "2022-05-27T14:58:28.220483Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 1, 1],\n",
       "       [3, 5, 3]])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "P = np.array([[1, 0],\n",
    "              [1, 1]])\n",
    "np.matmul(P, A) # 第$i$行乘$k$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "320b9ca8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T15:00:08.142234Z",
     "start_time": "2022-05-27T15:00:08.125279Z"
    }
   },
   "source": [
    "有了这三类矩阵之后，你可以构建一个矩阵$P = P_1P_2\\cdots C_k$，即等于一列初等矩阵的乘积，那么就可以实现对方程组的系数进行操作，例如对方程组交换两行后，将原来第一行（交换后的第二行）乘两倍，最后加到第二行上.\n",
    "\n",
    "我们先分开做一下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "bf276047",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T15:06:39.367141Z",
     "start_time": "2022-05-27T15:06:39.338242Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[4, 8, 4],\n",
       "       [5, 9, 5]])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.array([[1, 1, 1],\n",
    "              [2, 4, 2]])\n",
    "# 方程组交换两行\n",
    "P1 = np.array([[0, 1],\n",
    "              [1, 0]])\n",
    "A = np.matmul(P1, A)\n",
    "\n",
    "# 原来第一行（交换后的第二行）乘两倍\n",
    "P2 = np.array([[0, 1],\n",
    "              [2, 0]])\n",
    "A = np.matmul(P2, A)\n",
    "\n",
    "# 第一行加到第二行上\n",
    "P3 = np.array([[0, 1],\n",
    "              [1, 1]])\n",
    "A = np.matmul(P3, A)\n",
    "\n",
    "A"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1981a3c1",
   "metadata": {},
   "source": [
    "计算矩阵$P$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "efc21622",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T15:10:21.265205Z",
     "start_time": "2022-05-27T15:10:21.245100Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P = \n",
      " [[0 2]\n",
      " [1 0]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[4, 8, 4],\n",
       "       [1, 1, 1]])"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.array([[1, 1, 1],\n",
    "              [2, 4, 2]])\n",
    "\n",
    "P = np.matmul(P1, P2)\n",
    "P = np.matmul(P, P1)\n",
    "print(\"P = \\n\", P)\n",
    "\n",
    "np.matmul(P, A)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9fefb82",
   "metadata": {},
   "source": [
    "这里必须说一下，由于在方程中我们一般只做行变换，所以对应的是变换矩阵$P$在左边乘系数矩阵，称为：**左乘**. 在其他场景里，我们可以对矩阵进行列变换，那么相应的是**右乘**一个变换矩阵$P$.\n",
    "\n",
    "❗这里我们再次强调了为什么矩阵的乘法是一般是不能交换的，因为对应的含义完全不同！"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "553e2e78",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T15:16:05.767022Z",
     "start_time": "2022-05-27T15:16:05.746934Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "交换两行：\n",
      " [[3 4]\n",
      " [1 2]]\n",
      "交换两列：\n",
      " [[2 1]\n",
      " [4 3]]\n"
     ]
    }
   ],
   "source": [
    "A = np.array([[1, 2],\n",
    "              [3, 4]])\n",
    "P = np.array([[0, 1],\n",
    "              [1, 0]])\n",
    "\n",
    "print(\"交换两行：\\n\", np.matmul(P, A))\n",
    "print(\"交换两列：\\n\", np.matmul(A, P))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18cee272",
   "metadata": {},
   "source": [
    "这下我们知道了，矩阵就类似一种功能模块，我要对行执行这种功能，就左乘一种“功能”，要对列执行这种功能，就右乘“功能”."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4201aa10",
   "metadata": {},
   "source": [
    "事实上，对于任意一个线性方程组，我们都可以抽象成这样的形式\n",
    "$$Ax=b,$$\n",
    "其中，矩阵$A$是系数矩阵，$x$是由未知数构成的向量，$b$是常数向量.为了解这样的方程，凭借小学二年级的知识，我们很希望可以将$A$“除过去”变成$\\frac{b}{A}$，事实上这个写法是不对的，只是为了大家理解，在矩阵中我们没有定义除法，为了实现类似的功能，我们定义矩阵的逆.\n",
    "\n",
    "对于$n$阶方阵$A$，如果存在一个$n$阶方阵$B$，使得\n",
    "$$AB=BA=E_n$$\n",
    "则我们称$A$是可逆的，$B$是$A$的逆矩阵，记做$A^{-1}$.\n",
    "\n",
    "如果一个矩阵是可逆的，那么首先它一定要是个方阵，也就是行数等于列数，此外它还要满足行列式不等于0，也就是我们上面提到的**非奇异矩阵**.我们在此不给出严格的证明，这个可以联想除法去理解，当你要“除”过去，作为“分母”自然不能为0.\n",
    "\n",
    "至于如何计算，我们可以通过```Numpy```模块求解："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0b8acff5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-06-01T03:06:29.209066Z",
     "start_time": "2022-06-01T03:06:29.189120Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-2.0000000000000004 行列式不为0，非奇异阵\n",
      "A的逆矩阵：\n",
      " [[-2.   1. ]\n",
      " [ 1.5 -0.5]]\n",
      "验证AA_inv = E \n",
      " [[1.00000000e+00 1.11022302e-16]\n",
      " [0.00000000e+00 1.00000000e+00]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "A = np.array([[1, 2], [3, 4]])\n",
    "print(np.linalg.det(A),\"行列式不为0，非奇异阵\") # 检验是否奇异\n",
    "print(\"A的逆矩阵：\\n\", np.linalg.inv(A)) # 矩阵求逆\n",
    "\n",
    "A_inv = np.linalg.inv(A)\n",
    "\n",
    "print(\"验证AA_inv = E \\n\", np.matmul(A, A_inv))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "955705b8",
   "metadata": {},
   "source": [
    "这里看着不像单位阵，但实际上是因为数值计算带来的后果，我们仅需要做一下数值过滤即可.事实上，为了一些应用更加简便，对于非奇异阵我们也定义了\"伪逆\".\n",
    "它的定义是这样的：对于任意一个矩阵$A \\in \\mathbb{R}^{n\\times m}$，存在一个矩阵$A^g \\in \\mathbb{R}^{m\\times n}$，使得$AA^gA=A$，则称$A^g$为$A$的**伪逆**(广义逆).\n",
    "\n",
    "具体实现如下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "afc9ffab",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-06-01T03:15:23.411257Z",
     "start_time": "2022-06-01T03:15:23.396239Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0 行列式为0，奇异阵\n",
      "[[ 0.   0. ]\n",
      " [ 0.5 -0.5]]\n",
      "[[ 0.  1.]\n",
      " [ 0. -1.]]\n"
     ]
    }
   ],
   "source": [
    "B = np.array([[0, 1],\n",
    "              [0, -1]])\n",
    "print(np.linalg.det(B),\"行列式为0，奇异阵\") # 检验是否奇异\n",
    "# print(\"B的逆矩阵：\\n\", np.linalg.inv(B)) # 直接求逆会报错\n",
    "\n",
    "print(np.linalg.pinv(B))\n",
    "print(np.matmul(np.matmul(B, np.linalg.pinv(B)),B)) # 验证广义逆的定义"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca03e963",
   "metadata": {},
   "source": [
    "接下来我们来研究矩阵的功能，矩阵是如何发挥出它的功能的呢？事实上，矩阵作用的基本元素是向量，我们可以把矩阵$A$看成一个由$m$个$n$维向量组成的方块. 那么要研究矩阵的功能，最首要的是看它在每个向量上的作用. 对于向量而言，最基本的不外乎是平移跟拉伸.\n",
    "\n",
    "我们提及一个重要的核心概念：**向量在空间中的位置是绝对的，而其坐标值却是相对的，坐标的取值依托于其所选取的坐标向量（基底).** 更直白的说就是，对于同一个向量，选取的坐标向量（基底）不同，其所对应的坐标值就不同.(下图来源于石溪)\n",
    "\n",
    "![jupyter](./figures/2-3.jpeg)\n",
    "\n",
    "从中我们可以看到：向量$a$在直角坐标系下与在基底$e_1^{'},e_2^{'}$下的坐标显然是不同.\n",
    "\n",
    "假设一个向量在坐标系$\\mathbb{1}$下表示的坐标为$x$，当这个向量$x$经过一个线性变换形成一个新的向量$y$，用矩阵表示这个变换就是：$y = Ax$，矩阵$A$对应着$x \\rightarrow y$的线性变换. 同时，向量也可以在坐标系$\\mathbb{2}$下表示，其坐标为$x^{'}$，那么$x^{'} = Px$. 同理，$x^{'}$也可以经过同一个线性变换变成$y^{'}$，即：$y^{'} = Bx^{'}=BPx$. 最后我们把$y^{'}$转化为同一个坐标系下表达，即$y=P^{-1}y^{'}=P^{-1}BPx$. 因此，我们可以得到：$Ax = P^{-1}BPx$，即：\n",
    "$$\n",
    "A = P^{-1}BP\n",
    "$$\n",
    "我们称满足上式的矩阵A、B称为相似矩阵. 总结一下：一个向量在空间位置里，选取不同的坐标系，其坐标值是不同的. 对于空间中同一个线性变换，在不同的坐标系下，用于描述这个变换的矩阵也是不同的, 而这些不同矩阵所描述的线性变换是相似的，因此我们称他们为**相似矩阵**.\n",
    "\n",
    "那知道相似矩阵的概念有什么用呢？一个矩阵代表着一个线性变换，而不同的坐标系又会得到不同的相似矩阵，那我们能不能选用一个最佳的坐标系，使得我们描述的这个线性变换的矩阵是最佳的呢？什么矩阵才能称得上是最佳矩阵呢？答案就是**对角矩阵**！因为当我们同时需要经历很多次线性变换的时候，对角矩阵能极大的减少我们的计算量，即：\n",
    "$$\n",
    "A^{n}=\\left[\\begin{array}{lll}\n",
    "a_{1} & & \\\\\n",
    "& a_{2} & \\\\\n",
    "& & a_{3}\n",
    "\\end{array}\\right]^{n}=\\left[\\begin{array}{lll}\n",
    "a_{1}^{n} & & \\\\\n",
    "& a_{2}^{n} & \\\\\n",
    "& & a_{3}^{n}\n",
    "\\end{array}\\right]\n",
    "$$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "0ec2f8ab",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T15:59:40.543058Z",
     "start_time": "2022-05-27T15:59:40.522115Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 0, 0],\n",
       "       [0, 4, 0],\n",
       "       [0, 0, 9]])"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.array([[1, 0, 0],\n",
    "              [0, 2, 0], \n",
    "              [0, 0, 3]])\n",
    "np.matmul(A, A)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb882d57",
   "metadata": {},
   "source": [
    "那给你一组基，我们怎么将这组基转化成最优的基，即**对角矩阵**对应的基呢？【需要注意的是，并不是所有的矩阵都能相似于对角矩阵】\n",
    "\n",
    "首席按，我们的目标是：找到一个对角矩阵\n",
    "$\\Lambda=\\left[\\begin{array}{llll}\n",
    "\\lambda_{1} & & & \\\\\n",
    "& \\lambda_{2} & & \\\\\n",
    "& & \\cdots & \\\\\n",
    "& & & \\lambda_{n}\n",
    "\\end{array}\\right]$，使得\n",
    "$$P^{-1}AP = \\Lambda$$\n",
    "其中，矩阵 $P$ 和 $A$ 一样，均为 $n$ 阶方阵。\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95cf12cf",
   "metadata": {},
   "source": [
    "我们直接给出结论，我们找到的对角矩阵的这些元素$\\lambda_i$,称为矩阵$A$的特征值，特征值会满足如下的定义：\n",
    "$$Ax = \\lambda_i x$$\n",
    "其中，$x$是一个非零向量，称为$A$的特征值$\\lambda_i$对应的特征向量.\n",
    "\n",
    "Python 已经帮我们集成好计算的工具了，下面我们给出代码："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "8dbd1c2a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T16:39:36.547033Z",
     "start_time": "2022-05-27T16:39:36.528060Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "矩阵A的特征值为： [-1.  2.  2.]\n",
      "矩阵A的特征向量为：\n",
      " [[-0.70710678 -0.24253563  0.30151134]\n",
      " [ 0.          0.          0.90453403]\n",
      " [-0.70710678 -0.9701425   0.30151134]]\n",
      "矩阵A对角化为：\n",
      " [[-1.00000000e+00 -1.32062993e-16 -3.03478581e-16]\n",
      " [-1.60646788e-17  2.00000000e+00 -1.53475516e-17]\n",
      " [ 0.00000000e+00  0.00000000e+00  2.00000000e+00]]\n"
     ]
    }
   ],
   "source": [
    "# 使用python求解矩阵的特征值和特征向量\n",
    "A = np.array([[-2,1,1],\n",
    "             [0,2,0],\n",
    "             [-4,1,3]])\n",
    "lamb,p = np.linalg.eig(A)\n",
    "print(\"矩阵A的特征值为：\",lamb)\n",
    "print(\"矩阵A的特征向量为：\\n\",p)\n",
    "print(\"矩阵A对角化为：\\n\",np.matmul(np.linalg.inv(p),np.matmul(A,p)))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80da9f8b",
   "metadata": {},
   "source": [
    "需要注意一件事，如果我们采用```Numpy```计算，本质上是一种数值计算，计算的结果是接近真实值的一种数值逼近结果，所以你会发现```-1.32062993e-16```这些非常小的数值，你可以将其作为0看待，那么就可以得到相应的对角化矩阵了. 即：\n",
    "$\\Lambda=\\left[\\begin{array}{lll}\n",
    "-1 & &  \\\\\n",
    "& 2 & & \\\\\n",
    "& & 2 \\end{array}\\right]$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "8c0ea789",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T16:39:39.455177Z",
     "start_time": "2022-05-27T16:39:39.434236Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-1.  0.  0.]\n",
      " [ 0.  2.  0.]\n",
      " [ 0.  0.  2.]]\n"
     ]
    }
   ],
   "source": [
    "# 数值过滤\n",
    "res = np.matmul(np.linalg.inv(p),np.matmul(A,p))\n",
    "res[np.abs(res) <1e-6] = 0 # 将绝对值小于10的-6次方的值设为0\n",
    "print(res)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5a8e49e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T16:20:06.373732Z",
     "start_time": "2022-05-27T16:20:06.328804Z"
    }
   },
   "source": [
    "下面我们来讲其中的数学原理，看到数学就头晕目眩的同学可以跳过！\n",
    "\n",
    "为了方便分析和描述，我们把矩阵$P$写成一组列向量并排 排列的形式： $P=\\left[\\begin{array}{llll}p_{1} & p_{2} & \\ldots & p_{n}\\end{array}\\right]$, 即 $n$ 个 $n$ 维列向量的横向排列。根据$P^{-1}AP = \\Lambda$，我们左乘一个矩阵$P$，得到：$A P=P \\Lambda$，具体展开：\n",
    "$$\n",
    "A\\left[p_{1}, p_{2}, \\ldots, p_{n}\\right]=\\left[p_{1}, p_{2}, \\ldots, p_{n}\\right]\\left[\\begin{array}{llll}\n",
    "\\lambda_{1} & & & \\\\\n",
    "& \\lambda_{2} & & \\\\\n",
    "& & \\cdots & \\\\\n",
    "& & & \\lambda_{n}\n",
    "\\end{array}\\right]\n",
    "$$\n",
    "进而可以得到：$\\left[A p_{1}, A p_{2}, \\ldots, A p_{n}\\right]=\\left[\\lambda_{1} p_{1}, \\lambda_{2} p_{2}, \\ldots, \\lambda_{n} p_{n}\\right]$。那么问题的答案就出来了：为了上面这个等式能成立, 就必须让左右两边的向量在每个维度上分别相等。即, $A p_{1}=\\lambda_{1} p_{1}, \\quad A p_{2}=\\lambda_{2} p_{2}, \\ldots, \\quad A p_{n}=\\lambda_{n} p_{n}$ 。\n",
    "\n",
    "总结一下：\n",
    "\n",
    "第一步是：我们要找到满足上述等式$A p_{1}=\\lambda_{1} p_{1}, \\quad A p_{2}=\\lambda_{2} p_{2}, \\ldots, \\quad A p_{n}=\\lambda_{n} p_{n}$的这一组向量 $p_{1}, p_{2}, \\ldots, p_{n}$ 。找到他们之后，我们将其横向排列，就构成了我们苦心寻找的转换矩阵 $P=\\left[\\begin{array}{llll}p_{1} & p_{2} & \\ldots & p_{n}\\end{array}\\right]$;\n",
    "\n",
    "第二步是：将分别与向量 $p_{1}, p_{2}, \\ldots, p_{n}$ 对应的值 $\\lambda_{1}, \\lambda_{2}, \\ldots \\lambda_{n}$ 依序沿着对角线排列，就构成 了与矩阵 $A$ 相似的对角矩阵 $\\Lambda=\\left[\\begin{array}{cccc}\\lambda_{1} & & & \\\\ & \\lambda_{2} & & \\\\ & & . & \\\\ & & & \\lambda_{n}\\end{array}\\right]$ 。\n",
    "\n",
    "那么对角化的问题就直接转化为了：如何找到满足等式$A p_{1}=\\lambda_{1} p_{1}, \\quad A p_{2}=\\lambda_{2} p_{2}, \\ldots, \\quad A p_{n}=\\lambda_{n} p_{n}$的一组向量$p_{1}, p_{2}, \\ldots, p_{n}$和对应的值$\\lambda_1,\\lambda_2,...,\\lambda_n$。首先，我们的等式为：$Ap = \\lambda p$，那么$Ap = \\lambda Ip$，$I$为单位矩阵。我们稍作变形：$(A-\\lambda I)p = 0$，那么如果这个$p$是有解的话，那么$A-\\lambda I$的行列式$det(A-\\lambda I)=0$。因此我们只需要解这个方程$det(A-\\lambda I)=0$就可以求出$\\lambda$和向量$p$了。\n",
    "\n",
    "重点来了：我们把满足$Ap = \\lambda p$的数值$\\lambda$为矩阵$A$的特征值，称$p$为矩阵$A$关于特征值$\\lambda$的特征向量。那特征值和特征向量有什么意义呢？不难看出，由于$Ap = \\lambda p$，而一个矩阵对应一个线性变换，因此经过矩阵A变换后的向量竟然是原向量的伸缩，因此特征向量就是那些经过矩阵A变换后的向量方向与变换前的方向相同或者相反的向量。\n",
    "\n",
    "最后给一个例子给大家演示下怎么求特征值和特征向量吧！\n",
    "\n",
    "<div class=\"alert alert-info\" role=\"alert\">\n",
    "🌰举个例子：\n",
    "求矩阵 $\\boldsymbol{A}=\\left(\\begin{array}{ccc}-1 & 1 & 0 \\\\ -4 & 3 & 0 \\\\ 1 & 0 & 2\\end{array}\\right)$ 的特征值和特征向量.[采用两种方式计算python与手算]\n",
    "</div>\n",
    "\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "|A-\\lambda E| &=\\left|\\begin{array}{ccc}\n",
    "-1-\\lambda & 1 & 0 \\\\\n",
    "-4 & 3-\\lambda & 0 \\\\\n",
    "1 & 0 & 2-\\lambda\n",
    "\\end{array}\\right|=(2-\\lambda)\\left|\\begin{array}{cc}\n",
    "-1-\\lambda & 1 \\\\\n",
    "-4 & 3-\\lambda\n",
    "\\end{array}\\right| \\\\\n",
    "&=(2-\\lambda)(\\lambda-1)^{2}=0\n",
    "\\end{aligned}\n",
    "$$\n",
    "特征值为 $\\lambda=\\mathbf{2}, \\mathbf{1}, \\mathbf{1}$。\n",
    "\n",
    "把每个特征值 $\\boldsymbol{\\lambda}$ 代入线性方程组 $(A-\\lambda E) x=0$， 求出基础解系。当 $\\lambda=2$ 时, 解线性方程组 $(A-2 E) x=0$。\n",
    "$$\n",
    "(A-2 E)=\\left(\\begin{array}{lll}\n",
    "-3 & 1 & 0 \\\\\n",
    "-4 & 1 & 0 \\\\\n",
    "1 & 0 & 0\n",
    "\\end{array}\\right) \\rightarrow\\left(\\begin{array}{lll}\n",
    "1 & 0 & 0 \\\\\n",
    "0 & 1 & 0 \\\\\n",
    "0 & 0 & 0\n",
    "\\end{array}\\right)\n",
    "$$\n",
    "$\\left\\{\\begin{array}{l}x_{1}=0 \\\\ x_{2}=0\\end{array} \\quad\\right.$ 得基础解系: $p_{1}=\\left(\\begin{array}{l}0 \\\\ 0 \\\\ 1\\end{array}\\right)$\n",
    "\n",
    "[后续过程略]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "454f9988",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T16:23:47.002896Z",
     "start_time": "2022-05-27T16:23:46.984916Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "矩阵A的特征值为： [2. 1. 1.]\n",
      "矩阵A的特征向量为：\n",
      " [[ 0.          0.40824829  0.40824829]\n",
      " [ 0.          0.81649658  0.81649658]\n",
      " [ 1.         -0.40824829 -0.40824829]]\n"
     ]
    }
   ],
   "source": [
    "# 使用python求解矩阵的特征值和特征向量\n",
    "A = np.array([[-1,1,0],\n",
    "             [-4,3,0],\n",
    "             [1,0,2]])\n",
    "lamb,p = np.linalg.eig(A)\n",
    "print(\"矩阵A的特征值为：\",lamb)\n",
    "print(\"矩阵A的特征向量为：\\n\",p)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bfa6f9d",
   "metadata": {},
   "source": [
    "在刚刚的讨论中，我们了解了一种十分神奇的向量叫特征向量，这个向量可以在某个矩阵的变换下保持在同一直线上，也就是没有发生角度的偏转。那好奇的我们又开始想问题了，有没有一个矩阵是可以做到令一个向量进行旋转变换或者镜像变换呢？仔细思考下可以发现，这两种变换并没有改变向量的长度，而刚刚的特征向量反而与原向量的关系是拉伸（缩短）的关系。那令一个向量进行旋转变换或者镜像变换的矩阵是什么呢？答案就是：**正交矩阵**。\n",
    "\n",
    "如果满足以下等式的矩阵$A$称为正交矩阵：\n",
    "$$\n",
    "A^TA = AA^T = I\n",
    "$$\n",
    "通过上式，我们很快能知道：正交矩阵的逆矩阵与转置矩阵相同，即：$A^{-1} = A^T$，因为：$A^{-1}A=I$。同时，正交矩阵有一个非常好的性质：A的各行是单位向量且两两正交（垂直），又或者说A的各列是单位向量且两两正交（垂直），为什么呢？为了说明这个性质，我们将矩阵$A$分成n个行向量或者n个列向量，即：\n",
    "$$\n",
    "A=\\left(\\begin{array}{c}\n",
    "\\alpha_{1} \\\\\n",
    "\\alpha_{2} \\\\\n",
    "\\vdots \\\\\n",
    "\\alpha_{n}\n",
    "\\end{array}\\right)=\\left(\\beta_{1}, \\beta_{2}, \\cdots, \\beta_{n},\\right)\n",
    "$$\n",
    "\n",
    "因此，我们可以得到以下规律：\n",
    "   - $\\alpha_{i} \\cdot \\alpha_{i}^{T}=1$，也就是说$\\alpha_{i} $是单位向量。\n",
    "   - $\\alpha_{i} \\cdot \\alpha_{j}^{T}=0 \\quad(i \\neq j)$，向量之间两两正交。\n",
    "\n",
    "说到这里，已经有人能看出来，最简单的一个正交矩阵是单位矩阵，我们可以将它想象成一个坐标轴，而别的正交矩阵可以由这个坐标轴绕着原点进行旋转或者镜像得到，如图：\n",
    "![jupyter](./figures/2-4.png)\n",
    "\n",
    "到现在为止，我们已经很显然发现了一个结论：$det(A) = 1$或者$-1$，因为正交矩阵可以由坐标轴组成的正方体旋转或者镜像变换而来，行列式的绝对值描述了向量围成的面积/体积，因此正交矩阵的行列式要么是1，要么是-1。如果是数学推导的话，即：\n",
    "$$\n",
    "\\begin{aligned}\n",
    "&1=\\operatorname{det}(I)=\\operatorname{det}\\left(A^{T} A\\right)=\\operatorname{det}\\left(A^{T}\\right) \\operatorname{det}(A)=\\operatorname{det}(A)^{2} \\\\\n",
    "&\\Rightarrow \\operatorname{det}(A)=\\pm 1\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "因此给定一组基，我们怎么把他变成标准正交基呢？这里面用到的工具叫**施密特正交化(Gram-Schmidt)**，原理就是：我随便找一个原向量，把它固定住，接着找来第二个向量，往上面做投影，剩下的垂直分量就是第二个正交基，·····重复的做下去，直到所有基都变换过一遍后，得到的这组新的基就是正交基. 更进一步，如果我们把所有基进行标准化，使得每个基自己与自己做内积都为1，即模长为1，则得到的是一组标准正交基. 正交矩阵就为一个单位矩阵，就跟我们上面的解释完全吻合了. 下面给出施密特正交化的Pyhton代码： \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "ee043e18",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-05-27T16:37:59.282577Z",
     "start_time": "2022-05-27T16:37:59.272565Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 1.00000000e+00 -2.77731144e-16 -8.56351296e-17]\n",
      " [-2.77731144e-16  1.00000000e+00 -2.10355992e-16]\n",
      " [-8.56351296e-17 -2.10355992e-16  1.00000000e+00]]\n",
      "[[1. 0. 0.]\n",
      " [0. 1. 0.]\n",
      " [0. 0. 1.]]\n"
     ]
    }
   ],
   "source": [
    "# 施密特正交化(Gram-Schmidt)\n",
    "from scipy.linalg import *\n",
    "A = np.array([[1,2,3],\n",
    "              [2,1,3],\n",
    "              [3,2,1]])\n",
    "B = orth(A)  # 正交化，奇异值分解不是施密特正交化\n",
    "print(np.matmul(B,np.transpose(B)))   # 输出单位矩阵\n",
    "\n",
    "# 数值过滤\n",
    "res = np.matmul(B,np.transpose(B))\n",
    "res[np.abs(res) <1e-6] = 0 # 将绝对值小于10的-6次方的值设为0\n",
    "print(res)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58aba600",
   "metadata": {},
   "source": [
    "有了这些工具后，我们终于可以给Ginger家的智慧农场做点不一样的事情了.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ce20ac7",
   "metadata": {},
   "source": [
    "## 项目实战——基于矩阵变换的图像变换"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "afd1d751",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\" role=\"alert\">\n",
    "❓ 由于某些原因，Ginger发现家里的摄像头拍出来的图片是“倒了”的影像，但作为一个技术从业人员，她认为能用钱解决的事情一定不要用钱去解决. 因此她决定自己动手写一个小程序将这些图片恢复正常.\n",
    "</div>\n",
    "\n",
    "<img src=\"./figures/2-6.jpg\" width = \"200\" height = \"400\" div align=center />"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad03a168",
   "metadata": {},
   "source": [
    "我们先来看看每个点是怎么旋转的，首先我们建立一个平面直角坐标系，来观察向量的变换.\n",
    "\n",
    "<img src=\"./figures/2-7.png\" width = \"400\" height = \"400\" div align=center />\n",
    "\n",
    "我们给定一个向量$u=(3,2)$，将其逆时针旋转$90^{\\circ}$，可以得到向量$v=(-2,3)$.\n",
    "\n",
    "设初始向量$u=(x,y)$，逆时针旋转的角度为$\\alpha$. 此时可以推出，\n",
    "$$\n",
    "\\theta = \\arctan{\\frac{y}{x}} \\\\\n",
    "r = ||u||_2\n",
    "$$\n",
    "旋转后得到的坐标为\n",
    "$$\n",
    "x' = r\\cos{(\\theta + \\alpha)}\\\\\n",
    "y' = r\\sin{(\\theta + \\alpha)}\n",
    "$$\n",
    "利用三角和差公式得\n",
    "$$\n",
    "\\cos{(\\theta + \\alpha)} = \\cos{\\theta} \\cos{\\alpha}-\\sin{\\theta}\\sin{\\alpha}\\\\\n",
    "\\sin{(\\theta + \\alpha)} = \\sin{\\theta}\\cos{\\alpha} + \\cos{\\theta}\\sin{\\alpha}\n",
    "$$\n",
    "则\n",
    "$$\n",
    "\\begin{aligned}\n",
    "x' &= r\\cos{\\theta} \\cos{\\alpha}- r\\sin{\\theta}\\sin{\\alpha}\\\\\n",
    "&= x \\cos{\\alpha} - y \\sin{\\alpha}\\\\\n",
    "y' &= r\\sin{\\theta}\\cos{\\alpha} + r\\cos{\\theta}\\sin{\\alpha}\\\\\n",
    "&= y \\cos{\\alpha} + x \\sin{\\alpha}  \n",
    "\\end{aligned}\n",
    "$$\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "646524c9",
   "metadata": {},
   "source": [
    "\n",
    "$$\n",
    "\\left[\\begin{array}{lll}\n",
    "x' & y' & 1\n",
    "\\end{array}\\right]=\\left[\\begin{array}{lll}\n",
    "x & y & 1\n",
    "\\end{array}\\right]\\left[\\begin{array}{ccc}\n",
    "\\cos \\alpha & \\sin \\alpha & 0 \\\\\n",
    "-\\sin \\alpha & \\cos \\alpha & 0 \\\\\n",
    "0 & 0 & 1\n",
    "\\end{array}\\right]\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09c14754",
   "metadata": {},
   "source": [
    "但是转轴公式是旋转坐标轴\n",
    "\n",
    "$$\n",
    "\\left[\\begin{array}{lll}\n",
    "x' & y' & 1\n",
    "\\end{array}\\right]=\\left[\\begin{array}{lll}\n",
    "x & y & 1\n",
    "\\end{array}\\right]\\left[\\begin{array}{ccc}\n",
    "\\cos \\alpha & -\\sin \\alpha & 0 \\\\\n",
    "\\sin \\alpha & \\cos \\alpha & 0 \\\\\n",
    "0 & 0 & 1\n",
    "\\end{array}\\right]\n",
    "$$\n",
    "或者\n",
    "$$\n",
    "\\left[\\begin{array}{lll}\n",
    "x & y & 1\n",
    "\\end{array}\\right]=\\left[\\begin{array}{lll}\n",
    "x' & y' & 1\n",
    "\\end{array}\\right]\\left[\\begin{array}{ccc}\n",
    "\\cos \\alpha & -\\sin \\alpha & 0 \\\\\n",
    "\\sin \\alpha & \\cos \\alpha & 0 \\\\\n",
    "0 & 0 & 1\n",
    "\\end{array}\\right]\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5db6c59b",
   "metadata": {},
   "source": [
    "下面我们来尝试用python实现对二维向量的旋转："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d3ef3e34",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-06-02T16:11:49.666070Z",
     "start_time": "2022-06-02T16:11:49.647058Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.9999999999999998, 3.0)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 在------------位置补全代码\n",
    "import numpy as np\n",
    "from math import cos, sin, pi\n",
    "#逆时针为正\n",
    "def vec_2d(x0, y0, alpha):\n",
    "    \"\"\"\n",
    "    旋转2维向量.\n",
    "    x0: 横坐标.\n",
    "    y0: 纵坐标.\n",
    "    alpha: 旋转角度，弧度制.\n",
    "    return:(x,y) 旋转后的坐标.\n",
    "    \"\"\"\n",
    "    origin = np.array([[x0, y0, 1]])\n",
    "    Trans = np.array([[cos(alpha), sin(alpha), 0],\n",
    "                      [-sin(alpha), cos(alpha), 0],\n",
    "                      [0, 0, 1]])\n",
    "    \n",
    "    res =   origin.dot(Trans)\n",
    "    x = res[0][0]\n",
    "    y = res[0][1]\n",
    "    return (x, y)\n",
    "vec_2d(3, 2, pi/2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a26991a3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-06-02T09:37:02.632047Z",
     "start_time": "2022-06-02T09:37:02.623072Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2.0, -3.0)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 运行效果应该如下\n",
    "vec_2d(3, 2, -pi/2)   "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d03df09",
   "metadata": {},
   "source": [
    "但如果这样的话，会出现一个问题，对于一张图片而言，旋转中心在左上角，导致整张图片旋转不是中心旋转的. 下面我们需要对坐标轴进行平移，完善我们的变换公式"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6489aca",
   "metadata": {},
   "source": [
    "<img src=\"./figures/2-8.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e40e32a1",
   "metadata": {},
   "source": [
    "假设图片宽度为$W$，高度为$H$，则在第一个坐标系下(左图)的坐标$(x',y')$，变换之后的坐标为$(x'',y'')$，则\n",
    "$$\n",
    "\\begin{aligned}\n",
    "x'' &= x'- \\frac{1}{2}W \\\\\n",
    "y'' &= -y'+ \\frac{1}{2}H\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "则对应的矩阵表示为：\n",
    "\n",
    "<div class=\"alert alert-warning\" role=\"alert\">\n",
    "<h4>📋任务</h4> \n",
    "\n",
    "请你根据上式，补全下面矩阵中的问号处\n",
    "</div>\n",
    "\n",
    "$$\n",
    "\\left[\\begin{array}{lll}\n",
    "x'' & y'' & 1\n",
    "\\end{array}\\right]=\\left[\\begin{array}{lll}\n",
    "x' & y' & 1\n",
    "\\end{array}\\right]\\left[\\begin{array}{ccc}\n",
    "1 & 0 & 0 \\\\\n",
    "0 & -1 & 0 \\\\\n",
    "0.5 W & 0.5 H & 1\n",
    "\\end{array}\\right]\n",
    "$$\n",
    "\n",
    "同理可以求得其逆变换矩阵为：\n",
    "$$\n",
    "\\left[\\begin{array}{lll} \n",
    "x _{0} & Y _{0} & 1\n",
    "\\end{array}\\right]=\\left[\\begin{array}{lll} \n",
    "x & y & 1\n",
    "\\end{array}\\right]\\left[\\begin{array}{ccc}\n",
    "1 & 0 & 0 \\\\\n",
    "0 & -1 & 0 \\\\\n",
    "-0.5 W & 0.5 H & 1\n",
    "\\end{array}\\right]\n",
    "$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e41d8976",
   "metadata": {},
   "source": [
    "根据图像旋转的一般过程：\n",
    "1. 将原始图像的坐标系转换为数学坐标系；\n",
    "2. 通过旋转公式对冬像坐标进行旋转；\n",
    "3. 将旋转后的数学坐标系转换为图像坐标系.\n",
    "\n",
    "因此图像旋转的矩阵变换为：\n",
    "$$\n",
    "\\left[\\begin{array}{lll} \n",
    "x'' & y'' & 1\n",
    "\\end{array}\\right]=\\left[\\begin{array}{lll} \n",
    "x & y & 1\n",
    "\\end{array}\\right]\\left[\\begin{array}{ccc}\n",
    "1 & 0 & 0 \\\\\n",
    "0 & -1 & 0 \\\\\n",
    "-0.5 W & 0.5 H & 1\n",
    "\\end{array}\\right]\\left[\\begin{array}{ccc}\n",
    "\\cos \\alpha & -\\sin \\alpha & 0 \\\\\n",
    "\\sin \\alpha & \\cos \\alpha & 0 \\\\\n",
    "0 & 0 & 1\n",
    "\\end{array}\\right]\\left[\\begin{array}{ccc}\n",
    "1 & 0 & 0 \\\\\n",
    "0 & -1 & 0 \\\\\n",
    "0.5 W & 0.5H & 1\n",
    "\\end{array}\\right]\\\\\n",
    "=\\left[\\begin{array}{lll} \n",
    "x & y & 1\n",
    "\\end{array}\\right] \\left[\\begin{array}{ccc}\n",
    "\\cos \\alpha & \\sin \\alpha & 0 \\\\\n",
    "-\\sin \\alpha & \\cos \\alpha & 0 \\\\\n",
    "-0.5 W \\cos \\alpha +0.5 H \\sin \\alpha +0.5W & -0.5W \\sin \\alpha -0.5 H \\cos \\alpha + 0.5 H & 1\n",
    "\\end{array}\\right]\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "36d42410",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-06-02T18:04:29.873112Z",
     "start_time": "2022-06-02T18:04:29.863165Z"
    }
   },
   "outputs": [],
   "source": [
    "# 图像旋转的矩阵\n",
    "def Trans(x0, y0, W, H, alpha):\n",
    "    origin = np.array([[x0, y0, 1]])\n",
    "    res = origin.dot(np.array([[cos(alpha), sin(alpha), 0],\n",
    "                     [-sin(alpha), cos(alpha), 0],\n",
    "                     [-0.5*W*cos(alpha) + 0.5*H*sin(alpha) + 0.5*W, -0.5*W*sin(alpha) - 0.5*H*cos(alpha) + 0.5*H, 1]]))\n",
    "    return (int(res[0,:2][0]),int(res[0,:2][1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "19404de5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-06-02T18:04:31.664737Z",
     "start_time": "2022-06-02T18:04:31.386481Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(328, 400)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from skimage import io, data\n",
    "img3 = data.horse()\n",
    "io.imshow(img3)\n",
    "img3.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "bee0f909",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-06-02T18:04:37.505039Z",
     "start_time": "2022-06-02T18:04:35.078456Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x12b070280>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "img4 = np.zeros((400, 400))\n",
    "\n",
    "for x in range(img3.shape[0]):\n",
    "    for y in range(img3.shape[1]):\n",
    "        x1, y1 = Trans(x, y, 328, 400, pi/2)\n",
    "        img4[x1-355, y1] = img3[x, y] # 335是做了一步平移居中，保证画面完整性\n",
    "io.imshow(img4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92d44873",
   "metadata": {},
   "source": [
    "以上，我们理论出发，手把手带着你复现了图像旋转的流程，相信在这个过程中，你已经深刻的体会到了从理论，如何被应用到实际当中！当然，我们的实现过程是比较粗糙的，简单粗暴的！当你理解了一个理论工具后，如果你还将它实现了，更好的方式是把它封装成一个函数，放到你的代码库中，方便日后的使用！\n",
    "\n",
    "当然现在Python有很多现成的工具库，可以实现图像旋转的功能，例如```skimage```——一个图像处理库.\n",
    "\n",
    "<div class=\"alert alert-warning\" role=\"alert\">\n",
    "<h4>📋任务</h4> \n",
    "\n",
    "下面请你学习使用```skimage```内置函数```transform.rotate```，尝试一键旋转Ginger的农场里的小鸡！\n",
    "</div>\n",
    "\n",
    "文档地址：\n",
    "[transform.rotate](https://scikit-image.org/docs/stable/api/skimage.transform.html?highlight=transform%20rotate#skimage.transform.rotate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d915edba",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-06-10T18:35:35.001739Z",
     "start_time": "2022-06-10T18:35:13.707923Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x12a393310>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from skimage import io, transform\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "dirpath = \"./figures/2-6.jpg\"\n",
    "img = io.imread(dirpath) #读取数据\n",
    "plt.imshow(img) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "010deb5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x154ad3340>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 在#------------位置补全代码\n",
    "# 旋转图像\n",
    "from skimage import data\n",
    "from skimage.transform import rotate\n",
    "img2 = transform.rotate(img, 90,resize=True)\n",
    "plt.imshow(img2) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "106d358d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-06-02T17:56:40.536564Z",
     "start_time": "2022-06-02T17:56:35.906010Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x2048d277040>"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 不要运行本代码块！！！\n",
    "# 请保证运行完是如下结果"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79e17d6f",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-success\" role=\"alert\">\n",
    "  <h4 class=\"alert-heading\">Well done!</h4>\n",
    "  <p>恭喜你，完成了《线性代数》的学习，希望在日后的数模竞赛中，通过本课程的学习，你可以更加深刻的理解矩阵的强大之处，以及更多的使用向量化编程，提高代码的运行效率.</p>\n",
    "  <hr>\n",
    "  <p class=\"mb-0\">如有需要领取本次组队学习的答案，敬请关注公众号以及留意直播讲解！</p>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b3f46aa",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "author": "me",
  "kernelspec": {
   "display_name": "Python 3.9.12 ('base')",
   "language": "python",
   "name": "python3912jvsc74a57bd096f00530df6dbe9a09a68470253b0890ebe3f8d769efa151705a0922e1443c12"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autoclose": false,
   "autocomplete": true,
   "bibliofile": "biblio.bib",
   "cite_by": "apalike",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 1,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
   },
   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
